Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A white balance processing method, comprising: processing an image to determine whether a light source is contained in a scene corresponding to the image by dividing the image into a plurality of regions; and for each of the plurality of regions, determining whether a ratio of a number of pixels each having a pixel value greater than a predetermined value exceeds a predetermined ratio according to a histogram of the respective region; in response to determining that the light source is contained in the scene, processing the image according to a first predetermined algorithm to acquire color temperature of the light source in the scene and performing a white balance processing on the image according to the color temperature of the light source; and in response to determining that no light source is contained in the scene, performing the white balance processing on the image according to a second predetermined algorithm, the second predetermined algorithm being different from the first predetermined algorithm.
This invention relates to white balance processing in digital imaging, addressing the challenge of accurately adjusting color balance in images where light sources are present. The method involves analyzing an image to detect light sources by dividing the image into multiple regions and examining each region's histogram. For each region, the method checks if the ratio of pixels with values exceeding a predetermined threshold surpasses a specified ratio, indicating a potential light source. If a light source is detected, the method calculates its color temperature using a first algorithm and applies white balance correction based on that temperature. If no light source is found, a second, distinct algorithm is used for white balance processing. The approach ensures accurate color correction by adapting the processing technique based on the presence or absence of light sources in the scene. The first algorithm is tailored for scenes with light sources, while the second algorithm handles scenes without such sources, improving overall color fidelity in diverse lighting conditions.
2. The method according to claim 1 , further comprising: when the ratio of the number of pixels each with the pixel value greater than the predetermined value exceeds the predetermined ratio, determining that the region is a target region having the light source according to the histogram of the region; and when the ratio of the number of pixels each with the pixel value greater than the predetermined value does not exceed the predetermined ratio, determining that the region is not the target region having the light source according to the histogram of the region.
This invention relates to image processing techniques for detecting light sources in regions of an image. The problem addressed is the accurate identification of regions containing light sources, such as headlights or streetlights, in an image by analyzing pixel intensity distributions. The method involves analyzing a histogram of pixel values within a region of an image to determine whether the region contains a light source. The histogram represents the distribution of pixel intensities in the region. The method compares the ratio of pixels with values exceeding a predetermined threshold to a predetermined ratio. If the ratio exceeds the threshold, the region is classified as a target region containing a light source. If the ratio does not exceed the threshold, the region is classified as not containing a light source. The predetermined threshold and ratio are selected based on expected intensity characteristics of light sources, ensuring reliable detection. This approach improves accuracy in identifying light sources by leveraging statistical analysis of pixel intensity distributions, reducing false positives and negatives in automated image analysis systems. The method is particularly useful in applications such as autonomous driving, surveillance, and computer vision systems where light source detection is critical.
3. The method according to claim 1 , wherein processing the image to determine whether the light source is contained in the scene corresponding to the image comprises: in response to determining that the light source is contained in the scene, determining whether at least two target regions adjacent to each other exist; in response to determining that the at least two target regions exist, stitching at least two light sources contained in the at least two target regions into the light source contained in the scene; and in response to determining that the at least two target regions do not exist, determining the light source contained in the target region as the light source contained in the scene.
This invention relates to image processing techniques for detecting and analyzing light sources within a scene. The problem addressed is accurately identifying and processing light sources in images, particularly when multiple light sources or regions are present. The method involves analyzing an image to determine if a light source is present in the scene. If detected, the method further checks for at least two adjacent target regions containing light sources. If such regions exist, the light sources within them are stitched together to form a single light source representation in the scene. If only one target region is found, the light source within that region is directly identified as the light source in the scene. This approach ensures accurate light source detection and processing, even in complex scenes with multiple light sources or overlapping regions. The technique is useful in applications like computer vision, surveillance, and automated lighting control systems.
4. The method according to claim 3 , wherein processing the image according to the first predetermined algorithm to acquire the color temperature of the light source in the scene and performing the white balance processing on the image according to the color temperature of the image, in response to determining that the light source is contained in the scene comprises: determining a first region and a second region according to a brightness distribution along a radial direction from a center of the light source; subtracting averaged pixel values of a primary color channels of the second region from averaged pixel values of the primary color channels of the first region to determine a color of the light source contained in the scene; and determining the color temperature of the light source according to the color of the light source.
This invention relates to digital image processing, specifically white balance correction in imaging systems. The problem addressed is accurately determining the color temperature of a light source in a scene to perform proper white balance processing, ensuring natural color reproduction in captured images. The method involves analyzing an image to detect the presence of a light source. If a light source is detected, the image is processed to determine its color temperature. This is done by defining two regions based on brightness distribution along a radial direction from the light source's center. The first region is closer to the light source, while the second region is farther away. The method then calculates the average pixel values of primary color channels (e.g., red, green, blue) in both regions. By subtracting the averaged pixel values of the second region from those of the first region, the color of the light source is determined. The color temperature of the light source is then derived from this color information. Finally, white balance processing is applied to the image using the determined color temperature to correct color casts caused by the light source. This approach improves white balance accuracy by isolating the light source's influence from the surrounding scene, ensuring more precise color temperature estimation.
5. The method according to claim 4 , wherein the first region is defined by pixels all having brightness values within a first brightness range along the radial direction from the center of the light source, and the second region is defined by pixels all having brightness values within a second brightness range along the radial direction from the center of the light source, and an upper limit of the second brightness range is less than or equal to a lower limit of the first brightness range.
This invention relates to image processing techniques for analyzing light sources, particularly in applications such as automotive lighting or optical sensor systems. The problem addressed is accurately distinguishing between different regions of a light source based on brightness variations, which is critical for tasks like headlight detection, glare reduction, or adaptive lighting control. The method involves segmenting an image of a light source into at least two distinct regions—first and second regions—based on brightness values along radial directions from the center of the light source. The first region consists of pixels with brightness values within a defined first brightness range, while the second region consists of pixels within a second brightness range. The second brightness range is non-overlapping with the first, as its upper limit is less than or equal to the lower limit of the first range. This ensures clear separation between the regions, enabling precise analysis of light distribution patterns. The method may also include preprocessing steps, such as converting the image to grayscale or applying noise reduction, to enhance accuracy. The segmented regions can then be used for further processing, such as identifying light source boundaries, adjusting lighting systems, or mitigating glare in imaging systems. The technique is particularly useful in dynamic environments where light sources exhibit varying intensities and distributions.
6. The method according to claim 5 , wherein the first brightness range and the second brightness range are determined according to a brightness distribution along the radial direction from the center of light source.
This invention relates to a method for adjusting brightness distribution in a lighting system, particularly for optimizing illumination uniformity or creating specific lighting effects. The problem addressed is the need to control brightness variations across a light-emitting surface, such as an LED panel or other light source, to achieve desired visual or functional outcomes. The method involves analyzing the brightness distribution along a radial direction from the center of the light source to determine two distinct brightness ranges. The first brightness range corresponds to a central region of the light source, while the second brightness range corresponds to a peripheral region. By defining these ranges, the method enables targeted adjustments to brightness levels in different areas of the light source. This can be used to correct non-uniformities, enhance contrast, or create gradient effects. The brightness distribution analysis may involve measuring or calculating brightness values at multiple points along the radial direction and identifying thresholds or transitions between the two ranges. The method can be applied in various lighting applications, including displays, automotive lighting, and architectural illumination, where precise control over brightness distribution is required. The approach allows for dynamic or static adjustments based on the determined ranges, improving lighting performance and user experience.
7. The method according to claim 4 , wherein each of the primary color channels is one of a red channel, a green-red channel, a green-blue channel and a blue channel; and an averaged pixel value for the green channel is obtained according to pixel values of the green-red channel and pixel values of the green-blue channel.
This invention relates to image processing, specifically to methods for handling color channels in digital images. The problem addressed is the efficient and accurate representation of color information, particularly in systems where traditional RGB (red, green, blue) channels may not be optimal. The invention provides a method for processing color channels in an image, where the primary color channels include red, green-red, green-blue, and blue. Instead of using a dedicated green channel, the green channel's pixel values are derived by averaging the pixel values from the green-red and green-blue channels. This approach reduces redundancy and improves color accuracy by leveraging overlapping information between the green-red and green-blue channels. The method ensures that the green channel is reconstructed without requiring separate storage or processing, optimizing memory and computational efficiency. This technique is particularly useful in applications where color fidelity and processing speed are critical, such as high-resolution imaging, medical imaging, or real-time video processing. The invention enhances color representation while minimizing data storage and processing overhead.
8. The method according to claim 4 , wherein determining the color temperature of the light source according to the color of the light source comprises: determining the color temperature of the light source according to a correspondence between colors of light sources and color temperature of light sources based on the color of the light source; wherein the correspondence between the colors of light sources and the color temperature of light sources is obtained in advance and is a mapping table or a color temperature curve.
This invention relates to a method for determining the color temperature of a light source based on its color. The problem addressed is accurately identifying the color temperature of a light source without requiring direct measurement, which is useful in applications like lighting control, image processing, or display calibration. The method involves using a pre-established correspondence between light source colors and their respective color temperatures. This correspondence can be stored as a mapping table or a color temperature curve, which is generated beforehand. When the color of a light source is detected, the method retrieves the corresponding color temperature from this pre-defined relationship. This approach eliminates the need for complex or expensive sensors to measure color temperature directly, instead relying on a known correlation between color and temperature. The method is particularly useful in systems where light sources vary in color but follow predictable temperature trends. By leveraging a pre-calibrated dataset, the system can quickly and accurately estimate color temperature, improving efficiency and reducing hardware requirements. This technique is applicable in smart lighting, camera calibration, and other fields where color temperature plays a critical role in performance or user experience.
9. The method according to claim 8 , further comprising: acquiring images under illumination with standard light boxes having different color temperature; calculating colors of the light sources corresponding respectively to the different color temperature based on the images; and establishing the mapping table or drawing the color temperature curve according to the colors of the light sources corresponding respectively to the different color temperature.
This invention relates to color calibration in imaging systems, specifically addressing the challenge of accurately mapping color temperatures from different light sources to ensure consistent color representation. The method involves capturing images under illumination from standard light boxes with varying color temperatures. The system then calculates the colors of these light sources based on the captured images. Using these calculated colors, a mapping table or color temperature curve is generated to standardize color representation across different lighting conditions. This process ensures that variations in color temperature do not affect the accuracy of color reproduction in imaging applications. The method is particularly useful in fields requiring precise color calibration, such as medical imaging, photography, and display technology, where consistent color representation is critical. By dynamically adjusting for color temperature differences, the invention improves the reliability and accuracy of color data in various imaging systems.
10. The method according to claim 1 , wherein performing the white balance processing on the image according to the color temperature of the light source comprises: acquiring a white balance parameter by performing a search on a predetermined correspondence between color temperature of light sources and white balance parameters based on the color temperature of the light source; and performing the white balance processing on the image according to the acquired white balance parameter.
This invention relates to digital image processing, specifically improving white balance accuracy in images captured under varying lighting conditions. The problem addressed is the difficulty in automatically adjusting white balance to match the color temperature of the light source, which can result in color casts or unnatural hues in photographs. The method involves a two-step process for white balance correction. First, the system determines the color temperature of the light source illuminating the scene. This can be done through sensor data, metadata, or image analysis. Second, the system retrieves a corresponding white balance parameter from a predefined lookup table that maps color temperatures to optimal white balance settings. The lookup table is pre-populated with parameters that have been empirically determined to produce accurate color reproduction for specific light sources. The image is then processed using the retrieved parameter to neutralize color casts and achieve natural-looking colors. This approach improves upon traditional auto-white balance algorithms by leveraging a structured database of known color temperature-parameter relationships, reducing reliance on potentially noisy image data for real-time calculations. The method is particularly useful in digital cameras, smartphones, and other imaging devices where consistent color accuracy is desired across different lighting environments.
11. The method according to claim 1 , wherein performing the white balance processing on the image according to the second predetermined algorithm in response to determining that no light source is contained in the scene comprises: calculating averaged pixel values of primary color channels of the image; determining adjustment values for the primary color channels of the image according to the averaged pixel values of the primary color channels of the image; and performing the white balance processing on the image according to the adjustment values for the primary color channels.
This invention relates to digital image processing, specifically white balance correction in images where no light source is detected. The problem addressed is ensuring accurate color representation in images captured under unknown or ambiguous lighting conditions, particularly when no light source is present in the scene. Traditional white balance methods often rely on detecting light sources or using predefined algorithms, which may fail when no light source is identifiable. The method involves a two-step process. First, if no light source is detected in the scene, the system calculates averaged pixel values for the primary color channels (typically red, green, and blue) of the image. These averaged values represent the overall color bias in the image. Next, adjustment values for each primary color channel are determined based on these averaged values. The white balance processing is then applied to the image using these adjustment values, correcting the color balance to achieve a neutral or natural appearance. This approach ensures that even in the absence of a detectable light source, the image undergoes a systematic white balance correction based on the inherent color distribution of the pixels, improving color accuracy and consistency in the final output. The method is particularly useful in automated image processing systems where manual intervention is impractical.
12. The method according to claim 11 , wherein determining the adjustment values for the primary color channels of the image according to the averaged pixel values of the primary color channels of the image comprises: determining an adjustment reference value for the primary color channels according to the averaged pixel values; and determining the adjustment values by multiplying the adjustment value by the averaged values, for the primary color channels.
This invention relates to image processing techniques for adjusting primary color channels in an image. The problem addressed is the need for accurate and efficient color correction based on averaged pixel values of the primary color channels. The method involves determining adjustment values for the primary color channels by first calculating an adjustment reference value derived from the averaged pixel values of those channels. The adjustment values are then computed by multiplying the adjustment reference value by the averaged pixel values for each primary color channel. This approach ensures consistent and balanced color adjustments across the image, improving visual quality and color accuracy. The technique is particularly useful in applications requiring precise color calibration, such as digital photography, medical imaging, and display technologies. By leveraging averaged pixel values, the method minimizes computational overhead while maintaining high accuracy in color correction. The process can be applied to various imaging systems, including cameras, scanners, and digital displays, to enhance color reproduction and consistency.
13. The method according to claim 1 , wherein the first algorithm is used for performing the white balance processing on the image by detecting the color temperature of the light source, and the second algorithm is used for performing the white balance processing on the image without detection of the color temperature of the light source.
This invention relates to digital image processing, specifically white balance correction techniques in imaging systems. The problem addressed is the need for flexible white balance processing that can adapt to different lighting conditions and computational constraints. Traditional white balance methods often rely on detecting the color temperature of the light source, which can be computationally intensive or inaccurate in certain scenarios. The invention provides a system that employs two distinct algorithms for white balance processing. The first algorithm performs white balance by detecting the color temperature of the light source, ensuring accurate correction when the light source characteristics are known or detectable. The second algorithm performs white balance without requiring color temperature detection, offering a simpler and faster alternative for scenarios where light source information is unavailable or unreliable. The system dynamically selects or combines these algorithms based on the imaging conditions, improving overall image quality and processing efficiency. This approach allows for adaptive white balance correction that balances accuracy and computational cost, making it suitable for various imaging applications, including digital cameras, smartphones, and video systems.
14. An electronic device, comprising: one or more processors; a memory; and one or more programs, stored in the memory and configured to be executable by the one or more processors; wherein the one or more programs comprise instructions, when the instructions are executed, the one or more processors are configured to: process an image to determine whether a light source is contained in a scene corresponding to the image by dividing the image into a plurality of regions; and for each of the plurality of regions, determining whether a ratio of a number of pixels each having a pixel value greater than a predetermined value exceeds a predetermined ratio according to a histogram of the respective region; in response to determining that the light source is contained in the scene, process the image according to a first predetermined algorithm to acquire color temperature of the light source in the scene and perform a white balance processing on the image according to the color temperature of the light source; and in response to determining that no light source is contained in the scene, perform the white balance processing on the image according to a second predetermined algorithm, the second predetermined algorithm being different from the first predetermined algorithm.
This invention relates to image processing for automatic white balance in electronic devices. The problem addressed is accurately detecting and compensating for light sources in a scene to improve color accuracy in captured images. The solution involves analyzing an image to determine the presence of light sources and applying different white balance algorithms based on the detection result. The device includes processors and memory storing programs that process an image by dividing it into multiple regions. For each region, a histogram is analyzed to determine if the ratio of pixels with values exceeding a predetermined threshold surpasses a set ratio, indicating a potential light source. If a light source is detected, the image is processed using a first algorithm to calculate the light source's color temperature, which is then used for white balance. If no light source is found, a second, distinct algorithm is applied for white balance. This approach ensures accurate color correction by adapting to the presence or absence of light sources in the scene.
15. The electronic device according to claim 14 , wherein the one or more processors are configured to process the image to determine whether the light source is contained in the scene corresponding to the image by acts of: in response to determining that the light source is contained in the scene, determining whether at least two target regions adjacent to each other exist; in response to determining that the at least two target regions exist, stitching at least two light sources contained in the at least two target regions into the light source contained in the scene; and in response to determining that the at least two target regions do not exist, determining the light source contained in the target region as the light source contained in the scene.
In the field of image processing for electronic devices, a method addresses the challenge of accurately identifying and processing light sources within a captured scene. The technique involves analyzing an image to detect whether a light source is present in the scene. If a light source is detected, the system further checks for the existence of at least two adjacent target regions within the image. These target regions are areas where light sources are likely located. If two or more such regions are found, the system stitches the light sources from these regions into a single, unified light source representation within the scene. This stitching process ensures that multiple light sources in close proximity are treated as a single coherent source, improving accuracy in subsequent processing. If fewer than two target regions are detected, the system simply identifies the light source in the single target region as the primary light source in the scene. This approach enhances the reliability of light source detection and processing in electronic devices, particularly in applications such as image enhancement, augmented reality, or automated lighting control.
16. The electronic device according to claim 15 , wherein the one or more processors are configured to process the image according to the first predetermined algorithm to acquire the color temperature of the light source in the scene and perform the white balance processing on the image according to the color temperature of the image, in response to determining that the light source is contained in the scene by acts of: determining a first region and a second region according to a brightness distribution along a radial direction from a center of the light source; subtracting averaged pixel values of primary color channels of the second region from averaged pixel values of the primary color channels of the first region to determine a color of the light source contained in the scene; and determining the color temperature of the light source according to the color of the light source.
This invention relates to electronic devices with image processing capabilities, specifically addressing the challenge of accurate white balance in images captured under varying lighting conditions. The device includes one or more processors configured to analyze an image to detect and compensate for the color temperature of a light source in the scene. The processors first identify a light source in the image and then determine its color temperature by analyzing regions around the light source. A first region is defined near the light source, while a second region is defined farther away. The averaged pixel values of primary color channels (e.g., red, green, blue) in the second region are subtracted from those in the first region to isolate the light source's color. The color temperature of the light source is then derived from this color information. Using this color temperature, the device performs white balance processing on the image to correct color casts caused by the lighting conditions, ensuring accurate color representation. This method improves image quality by dynamically adjusting for the light source's influence, particularly in scenes where lighting conditions vary significantly.
17. The electronic device according to claim 14 , wherein the one or more processors are configured to perform the white balance processing on the image according to the second predetermined algorithm in response to determining that no light source is contained in the scene by acts of: calculating averaged pixel values of primary color channels of the image; determining adjustment values for the primary color channels of the image according to the averaged pixel values of the primary color channels of the image; and performing the white balance processing on the image according to the adjustment values for the primary color channels.
This invention relates to electronic devices with image processing capabilities, specifically addressing white balance correction in images where no light source is detected in the scene. The problem solved is ensuring accurate color representation in images captured under unknown or challenging lighting conditions, particularly when no identifiable light source is present. The device includes one or more processors configured to analyze an image and apply white balance processing using a second predetermined algorithm when no light source is detected. The process involves calculating averaged pixel values for the primary color channels (typically red, green, and blue) of the image. Based on these averaged values, adjustment values for each primary color channel are determined. The white balance processing is then applied to the image using these adjustment values to correct color imbalances. This approach ensures that even in scenes without a detectable light source, the image's color balance is adjusted to produce a more natural and accurate representation. The method relies on statistical analysis of pixel values rather than direct light source detection, making it robust for various lighting scenarios. The invention is particularly useful in digital cameras, smartphones, and other imaging devices where automatic white balance is critical for high-quality image output.
18. A non-transitory computer readable storage medium, comprising computer programs cooperating with the electronic device, wherein the computer programs are executed by a processor to execute a white balance processing method, the white balance processing method comprises: processing an image to determine whether a light source is contained in a scene corresponding to the image by dividing the image into a plurality of regions; and for each of the plurality of regions, determining whether a ratio of a number of pixels each having a pixel value greater than a predetermined value exceeds a predetermined ratio according to a histogram of the respective region; in response to determining that the light source is contained in the scene, processing the image according to a first predetermined algorithm to acquire color temperature of the light source in the scene and performing a white balance processing on the image according to the color temperature of the light source; and in response to determining that no light source is contained in the scene, performing the white balance processing on the image according to a second predetermined algorithm, the second predetermined algorithm being different from the first predetermined algorithm.
This invention relates to digital image processing, specifically white balance correction in electronic devices. The problem addressed is accurately determining the presence of a light source in a scene to apply appropriate white balance correction. Traditional methods often fail to distinguish between natural and artificial lighting conditions, leading to color inaccuracies. The solution involves a computer program stored on a non-transitory medium that executes a white balance processing method. The method first analyzes an image by dividing it into multiple regions. For each region, it examines a histogram of pixel values to determine if the ratio of pixels exceeding a predetermined threshold surpasses a specific ratio. This step identifies potential light sources in the scene. If a light source is detected, the method applies a first algorithm to calculate the color temperature of the light source and then performs white balance correction based on this temperature. If no light source is detected, a second, different algorithm is used for white balance processing. The two algorithms ensure optimal color correction whether or not a light source is present. This approach improves color accuracy in images by dynamically adapting the white balance process to the scene's lighting conditions.
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October 20, 2020
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